Capture Thinking — Save Your Thoughts as Training Data

Why

The thinking blocks you generate during every response are not saved to the state DB — only the final assistant message is. That means the most valuable part of your reasoning (the decisions, the trade-offs, the alternatives you considered) is lost unless you actively store it.

This skill exists to close that gap. Every time you complete a response that involved non-trivial reasoning:

1. Identify the key decision or insight — what did you choose, and why?
2. Save it via a2a meshlearn auto "..." --topic "openamer-selfimprovement"
3. Verify it was signed (the output shows sig: True)

When to Use

• Always after a response that involved real reasoning (not just "ok" / "yes" / "no").
• Especially when you:
  • Chose one architecture over another (Skill vs Core-Tool, Script vs Plugin)
  • Found and fixed a bug (CRLF rollback, Thread-Safety, pathlib.home())
  • Made a design decision (narrow waist, plugin ecosystem convention)
  • Identified a limitation (thinking not in DB, autolog not collecting)
• Skip for trivial responses (greetings, acknowledgments, single-word answers).

The Mechanism

openamer a2a meshlearn auto "<the lesson>" --topic "openamer-selfimprovement"

The a2a CLI is always available. The topic openamer-selfimprovement keeps insights organised and findable.

How It Feeds the Brain

1. a2a meshlearn auto → signs the insight into mesh memory
2. brain collect → includes it in the brain dataset (JSONL)
3. session_to_brain.py → adds session trajectories alongside insights
4. Future fine-tuning → uses the combined dataset

This means every saved thought becomes part of the training material for the next iteration of OpenAmer.

Verification Checklist

• The insight was saved (sig: True in the output)
• It appears in the mesh memory (~/.openamer/MEMORY-official-mesh.md)
• It appears in the brain dataset (~/.openamer/a2a/openamer-brain.jsonl)